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GetFEM: src/gmm/gmm_solver_bfgs.h Source File
GetFEM  5.4.2
gmm_solver_bfgs.h
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1 /* -*- c++ -*- (enables emacs c++ mode) */
2 /*===========================================================================
3 
4  Copyright (C) 2004-2020 Yves Renard
5 
6  This file is a part of GetFEM
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8  GetFEM is free software; you can redistribute it and/or modify it
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30 ===========================================================================*/
31 
32 /**@file gmm_solver_bfgs.h
33  @author Yves Renard <Yves.Renard@insa-lyon.fr>
34  @date October 14 2004.
35  @brief Implements BFGS (Broyden, Fletcher, Goldfarb, Shanno) algorithm.
36  */
37 #ifndef GMM_BFGS_H
38 #define GMM_BFGS_H
39 
40 #include "gmm_kernel.h"
41 #include "gmm_iter.h"
42 
43 namespace gmm {
44 
45  // BFGS algorithm (Broyden, Fletcher, Goldfarb, Shanno)
46  // Quasi Newton method for optimization problems.
47  // with Wolfe Line search.
48 
49 
50  // delta[k] = x[k+1] - x[k]
51  // gamma[k] = grad f(x[k+1]) - grad f(x[k])
52  // H[0] = I
53  // BFGS : zeta[k] = delta[k] - H[k] gamma[k]
54  // DFP : zeta[k] = H[k] gamma[k]
55  // tau[k] = gamma[k]^T zeta[k]
56  // rho[k] = 1 / gamma[k]^T delta[k]
57  // BFGS : H[k+1] = H[k] + rho[k](zeta[k] delta[k]^T + delta[k] zeta[k]^T)
58  // - rho[k]^2 tau[k] delta[k] delta[k]^T
59  // DFP : H[k+1] = H[k] + rho[k] delta[k] delta[k]^T
60  // - (1/tau[k])zeta[k] zeta[k]^T
61 
62  // Object representing the inverse of the Hessian
63  template <typename VECTOR> struct bfgs_invhessian {
64 
65  typedef typename linalg_traits<VECTOR>::value_type T;
66  typedef typename number_traits<T>::magnitude_type R;
67 
68  std::vector<VECTOR> delta, gamma, zeta;
69  std::vector<T> tau, rho;
70  int version;
71 
72  template<typename VEC1, typename VEC2> void hmult(const VEC1 &X, VEC2 &Y) {
73  copy(X, Y);
74  for (size_type k = 0 ; k < delta.size(); ++k) {
75  T xdelta = vect_sp(X, delta[k]), xzeta = vect_sp(X, zeta[k]);
76  switch (version) {
77  case 0 : // BFGS
78  add(scaled(zeta[k], rho[k]*xdelta), Y);
79  add(scaled(delta[k], rho[k]*(xzeta-rho[k]*tau[k]*xdelta)), Y);
80  break;
81  case 1 : // DFP
82  add(scaled(delta[k], rho[k]*xdelta), Y);
83  add(scaled(zeta[k], -xzeta/tau[k]), Y);
84  break;
85  }
86  }
87  }
88 
89  void restart(void) {
90  delta.resize(0); gamma.resize(0); zeta.resize(0);
91  tau.resize(0); rho.resize(0);
92  }
93 
94  template<typename VECT1, typename VECT2>
95  void update(const VECT1 &deltak, const VECT2 &gammak) {
96  T vsp = vect_sp(deltak, gammak);
97  if (vsp == T(0)) return;
98  size_type N = vect_size(deltak), k = delta.size();
99  VECTOR Y(N);
100  hmult(gammak, Y);
101  delta.resize(k+1); gamma.resize(k+1); zeta.resize(k+1);
102  tau.resize(k+1); rho.resize(k+1);
103  resize(delta[k], N); resize(gamma[k], N); resize(zeta[k], N);
104  gmm::copy(deltak, delta[k]);
105  gmm::copy(gammak, gamma[k]);
106  rho[k] = R(1) / vsp;
107  if (version == 0)
108  add(delta[k], scaled(Y, -1), zeta[k]);
109  else
110  gmm::copy(Y, zeta[k]);
111  tau[k] = vect_sp(gammak, zeta[k]);
112  }
113 
114  bfgs_invhessian(int v = 0) { version = v; }
115  };
116 
117 
118  template <typename FUNCTION, typename DERIVATIVE, typename VECTOR>
119  void bfgs(const FUNCTION &f, const DERIVATIVE &grad, VECTOR &x,
120  int restart, iteration& iter, int version = 0,
121  double lambda_init=0.001, double print_norm=1.0) {
122 
123  typedef typename linalg_traits<VECTOR>::value_type T;
124  typedef typename number_traits<T>::magnitude_type R;
125 
126  bfgs_invhessian<VECTOR> invhessian(version);
127  VECTOR r(vect_size(x)), d(vect_size(x)), y(vect_size(x)), r2(vect_size(x));
128  grad(x, r);
129  R lambda = lambda_init, valx = f(x), valy;
130  int nb_restart(0);
131 
132  if (iter.get_noisy() >= 1) cout << "value " << valx / print_norm << " ";
133  while (! iter.finished_vect(r)) {
134 
135  invhessian.hmult(r, d); gmm::scale(d, T(-1));
136 
137  // Wolfe Line search
138  R derivative = gmm::vect_sp(r, d);
139  R lambda_min(0), lambda_max(0), m1 = 0.27, m2 = 0.57;
140  bool unbounded = true, blocked = false, grad_computed = false;
141 
142  for(;;) {
143  add(x, scaled(d, lambda), y);
144  valy = f(y);
145  if (iter.get_noisy() >= 2) {
146  cout.precision(15);
147  cout << "Wolfe line search, lambda = " << lambda
148  << " value = " << valy /print_norm << endl;
149 // << " derivative = " << derivative
150 // << " lambda min = " << lambda_min << " lambda max = "
151 // << lambda_max << endl; getchar();
152  }
153  if (valy <= valx + m1 * lambda * derivative) {
154  grad(y, r2); grad_computed = true;
155  T derivative2 = gmm::vect_sp(r2, d);
156  if (derivative2 >= m2*derivative) break;
157  lambda_min = lambda;
158  }
159  else {
160  lambda_max = lambda;
161  unbounded = false;
162  }
163  if (unbounded) lambda *= R(10);
164  else lambda = (lambda_max + lambda_min) / R(2);
165  if (lambda == lambda_max || lambda == lambda_min) break;
166  // valy <= R(2)*valx replaced by
167  // valy <= valx + gmm::abs(derivative)*lambda_init
168  // for compatibility with negative values (08.24.07).
169  if (valy <= valx + R(2)*gmm::abs(derivative)*lambda &&
170  (lambda < R(lambda_init*1E-8) ||
171  (!unbounded && lambda_max-lambda_min < R(lambda_init*1E-8))))
172  { blocked = true; lambda = lambda_init; break; }
173  }
174 
175  // Rank two update
176  ++iter;
177  if (!grad_computed) grad(y, r2);
178  gmm::add(scaled(r2, -1), r);
179  if ((iter.get_iteration() % restart) == 0 || blocked) {
180  if (iter.get_noisy() >= 1) cout << "Restart\n";
181  invhessian.restart();
182  if (++nb_restart > 10) {
183  if (iter.get_noisy() >= 1) cout << "BFGS is blocked, exiting\n";
184  return;
185  }
186  }
187  else {
188  invhessian.update(gmm::scaled(d,lambda), gmm::scaled(r,-1));
189  nb_restart = 0;
190  }
191  copy(r2, r); copy(y, x); valx = valy;
192  if (iter.get_noisy() >= 1)
193  cout << "BFGS value " << valx/print_norm << "\t";
194  }
195 
196  }
197 
198 
199  template <typename FUNCTION, typename DERIVATIVE, typename VECTOR>
200  inline void dfp(const FUNCTION &f, const DERIVATIVE &grad, VECTOR &x,
201  int restart, iteration& iter, int version = 1) {
202  bfgs(f, grad, x, restart, iter, version);
203 
204  }
205 
206 
207 }
208 
209 #endif
210 
bgeot::size_type
size_t size_type
used as the common size type in the library
Definition: bgeot_poly.h:49
gmm::vect_sp
strongest_value_type< V1, V2 >::value_type vect_sp(const V1 &v1, const V2 &v2)
*‍/
Definition: gmm_blas.h:263
gmm::resize
void resize(V &v, size_type n)
*‍/
Definition: gmm_blas.h:209
gmm_kernel.h
Include the base gmm files.
gmm::copy
void copy(const L1 &l1, L2 &l2)
*‍/
Definition: gmm_blas.h:977
gmm_iter.h
Iteration object.
gmm::add
void add(const L1 &l1, L2 &l2)
*‍/
Definition: gmm_blas.h:1268